Description
Random Data Generator
a Univariate gaussian data generator
o Input
Expectation value or mean: m
Variance: s
o Output: A data point trom N(m, s)
0 HINT
You nave to handcraft your geneartor based on one ottne approaches given in the
hyperlink.
You can use uniform distribution function (Numpy)
t). Polynomial basis linear model data generator
W is an x 1 vector
o Input: n (basis number), a, w
- wo:ro +
o Output: y (a number)
o Internal constraint
1.0
1.0
a: is uniformly distributed.
Sequential Estimator
Sequential estimate the mean and variance
o Data is given trom the univariate qaussian data generator (1 *a).
Input: (1 .a) Function:
Call (1 to get a new data point trom N(m, s)
o Use sequential estimation to find the current estimates to m and s
